Registering mr patient data on the basis of generic models

ABSTRACT

A method for registering a non-patient-characteristic three-dimensional magnetic resonance data set (MR data set) to patient-characteristic data includes: producing or providing a non-patient-characteristic three-dimensional generic model of a body or body part containing body structure data; ascertaining or providing two-dimensional patient-characteristic detection data of a patient; using a transformation protocol for data-linking the body structure data of the three-dimensional generic model to the two-dimensional patient-characteristic detection data to change or adapt the generic model of the body or body part based on the ascertained two-dimensional patient-characteristic detection data, wherein the three-dimensional generic model is at least correlated with a three-dimensional MR reference data set; and changing or deforming at least a part of the three-dimensional MR reference data set by using the transformation protocol to generate a patient-characteristic three-dimensional MR data set that is registered to the fluoroscopic images.

RELATED APPLICATION DATA

This application claims priority of U.S. Provisional Application No.60/822,706 filed on Aug. 17, 2006, which is incorporated herein byreference in its entirety.

FIELD OF THE INVENTION

The present invention relates to a method and device for registering anon-patient-characteristic three-dimensional magnetic resonance (MR)data set to patient-characteristic image data, and more particularly, toat least two fluoroscopic images of the patient. Based on these imagedata, it is then possible to perform computer-assisted medicalnavigation.

BACKGROUND OF THE INVENTION

When examining a patient or preparing for surgery, in particular surgeryin the region of bones such as, for example, spine, hip joint or kneeoperations, x-ray recordings or computer tomography (CT) recordings ofthe affected body structure are taken. From these recordings, the bodystructures can be clearly displayed. A drawback to such methods,however, is that x-ray radiation used to generate the images can be aburden to the patient's health.

Magnetic resonance or nuclear spin tomography recordings (MR recordings)can be produced without any burden to the health of a patient. Suchimaging techniques are suitable for displaying soft tissue. Bonestructures, however, generally are poorly identified or not identifiablein MR recordings.

In order to display both bone structures and soft tissues, it may benecessary to register or fuse CT recordings or x-ray recordings to MRrecordings of a patient. This, however, can incur significant costssince computer tomographs and magnetic resonance tomographs are veryexpensive both to purchase, maintain and operate. Further, a pluralityof CT recordings typically are produced, which can place a highradiation load on the patient.

Attempts have been made to develop systems that can be used withoutseparately detected patient body structure data, for example on thebasis of generic models of image data sets for body structures. However,such systems can lack the required accuracy for the patient to betreated in each case.

EP 1 348 394 relates to a method for computer-assisted, medicalnavigation in which the current position of a patient or part of apatient's body and the positions of medical treatment apparatus ortreatment-assisting apparatus are detected by means of a positiondetection unit. The detected position data are assigned to bodystructure data in order to jointly use the body structure data andassigned position data within the framework of treatment assistance.Body structure data are used that are obtained on the basis of athree-dimensional generic model, wherein the model is adapted bydata-linking on a two-dimensional plane with patient-characteristic,two-dimensional detection data.

These generic models, however, are not primarily based on MR data sets.Therefore, generic MR data cannot be correspondingly deformed andregistered to the fluoroscopic images.

SUMMARY OF THE INVENTION

In a method for registering a non-patient-characteristicthree-dimensional magnetic resonance (MR) data set topatient-characteristic image data, such as with image data of at leasttwo fluoroscopic images of a patient, a three-dimensional generic orstatistical model, in particular a surface model, of a body or body partis produced or provided. CT recordings, MR recordings, x-ray recordingsor other images recorded by means of medical imaging systems, forexample of average bodies or body parts, or of a particular group suchas persons of a particular size or age, can be used to generate thegeneric or statistical model. These recordings can be stored in adatabase and retrieved in order to generate the generic or statisticalmodel. Generic or statistical models that have already been producedand, for example, are based on body parts or body structures of aparticular person sub-group also can be used. The generic or statisticalmodels can be surface models of a body or body part.

Two-dimensional patient-characteristic detection data of a patient alsocan be ascertained, for example, by recording or providing at least twofluoroscopic images of the patient. The fluoroscopic images of thepatient may have been recorded during previous examinations and/orsurgery and stored in a database.

The non-patient-specific three-dimensional generic model, for example,maps the typical shape and/or structure of a body or body part and canbe based on body parts or body structures of a plurality of persons and,thus, is not specific to a particular body or patient. Thepatient-specific fluoroscopic recordings contain patient-specifictwo-dimensional image data which are characteristic of a particular bodyor patient.

The generic model is adapted to the two-dimensional patient-specificfluoroscopic image data or patient-characteristic detection data. Theimage data or body structure data of the generic model can be adapted tothe two-dimensional patient-characteristic detection data by means of atransformation protocol. In other words, the image data of the genericmodel can be deformed or changed in order to ensure an approximation ofthe three-dimensional generic model or of a two-dimensional projectionof the generic model to the patient-specific detection data.

One way of adapting the generic model to the patient-specific detectiondata, such as the at least two patient-specific fluoroscopic image datasets, is described in the European patent application number 06012256,belonging to the Assignee of the present application, entitled “Shapereconstruction using x-ray images”, the contents of which is herebyincorporated by reference in its entirety. According to EP 06012256, ageneral three-dimensional model of a structure is obtained, at least twotwo-dimensional images of the structure are obtained, and at least oneimage feature in the image is determined. The orientation of the generalthree-dimensional model of the structure with respect to the at leasttwo two-dimensional images of the structure is determined such that theat least one image feature of a two-dimensional projection of thethree-dimensional model matches the two-dimensional image feature or isvery similar to it. Once the orientation of the three-dimensional modelhas been determined, the three-dimensional model is morphed or deformedin order to adapt the shape of the three-dimensional model to the atleast two two-dimensional images.

In accordance with the methods, there is a correlation between thegeneric model and, for example, at least one generic, average or typicalMR reference data set of a body or body part or body structure. Thegeneric model preferably is at least based on the at least one MRreference data set and, in particular, also can be based on otherreference data sets, such as CT reference data sets.

By adapting the generic model or the two-dimensional projection of thegeneric model onto the patient-specific fluoroscopic image data, atransformation protocol can be obtained, by means of which the bodystructure data of the generic model may be changed or deformed. At leasta part of the three-dimensional MR reference data set can be deformed orchanged by means of this transformation protocol. The MR reference dataset thus can be adapted to the patient-specific or body-specificfluoroscopic image data. A patient-characteristic three-dimensional MRdata set that is adapted to or registered to the fluoroscopic imagesthus can be generated or ascertained from the MR reference data set.

Both the at least partially adapted generic model and an at leastpartially patient-characteristic three-dimensional MR data set generatedtherefrom or corresponding thereto also can be linked to anotherpatient-characteristic three-dimensional MR data set by a rigidtransformation. This can enable navigation based onpatient-characteristic three-dimensional MR data.

An advantage of the method is that when a generic or statistical modelis used that has been adapted to the patient, it is no longer necessary,for a treatment in which medical navigation is to be provided, toproduce a separate data set for the body structure. On the one hand,this spares the patient a high radiation load, for example fromrecording numerous x-ray or CT images, and on the other hand, the costof producing such data sets can be minimized. Further, linking thegeneric body structure data with patient-characteristic detection dataprovides a data set that can be used to provide very accurate medicalnavigation. The generic model, which can be a universal model for therelevant body structure that includes all relevant data, does not fromthe outset comprise any data that are specifically tailored to therelevant patient. The generic model, however, once adapted with the aidof patient-characteristic detection data, does comprise sufficientanatomical or body structure data to provide a sufficiently accuratebasis for medical navigation.

It is possible to work with the adapted image data set or model as withan image data set of the patient that is pre-operatively produced atsignificant cost and radiation load. For example, it is conceivable touse a generic model that comprises a typical or average body structure,for example a simple model representation of a vertebra, upper arm bone,lower arm bone, upper leg bone, lower leg bone or pelvic bone or otherosseous body structure and/or soft tissue structure. The generic modelalso can comprise a statistical model of the body structure, inparticular based on statistical evaluations of an indefinite number ofimage data sets, for example actual vertebra image data sets.

There also exists the possibility of directly providing the genericmodel as a kind of package of models for a plurality of body structuresof the same type. In such a case, it is possible when adapting the modelto select, from the plurality of models in the package, the one whichbest fits the patient-characteristic detection data, such that the modelonly need be slightly adapted (e.g., with computer assistance).

The generic model can comprise a two-dimensional or three-dimensionaldata set of a body structure, and in particular a geometric model. Inother words, the generic model can be both three-dimensional data (forexample, a vertebra model) and two-dimensional data (for example,virtual x-ray images) or also a model in the form of geometric data.These data, for example, can be angles and/or trajectory informationthat is displayed to the physician and indicates to the physician theideal position of an implant.

The generic model can be correlated with at least one MR reference dataset, such that changes or deformations of adaptations of the genericmodel by means of the transformation protocol can be applied analogouslyto the at least one MR reference data set. This enables the MR referencedata set to be changed so as to generate an MR data set that is at leastalmost patient-characteristic.

The generic model also can be formed from at least one three-dimensionalCT reference data set and the at least one three-dimensional MRreference data set. In this manner, the CT reference data set and the MRreference data set can so to speak form three-dimensional CT referencerepresentations, CT reference models, MR reference representationsand/or MR reference models corresponding to the generic model, whereinthe corresponding CT and MR reference data sets preferably areregistered to each other.

The generic or statistical model can be formed from a plurality of CTreference data sets and a plurality of corresponding MR data sets thatare or can be registered to each other.

A plurality of CT reference data sets preferably are ascertained orprovided in order to form the generic model. Also, MR reference datasets corresponding to the plurality of CT reference data sets preferablyare ascertained or provided, and the MR reference data sets preferablyare registered to their corresponding CT reference data sets. Thegeneric model can be produced, for example, as a surface model fromthese data sets that are registered to each other, wherein a CTreference model can be produced from the plurality of CT reference datasets and an MR reference model can be produced from the plurality of MRreference data sets. These data sets can be correlated with the genericmodel or definitively assigned, or underlie the generic model.

If the generic model is deformed due to being adapted to thepatient-specific image data or detection data, this deformation obeys atransformation protocol or mapping protocol. By deforming the genericmodel, a model that is adapted to the actual body structures of thepatient can be produced. If the transformation protocol is applied tothe MR reference data sets that are correlated with the generic model,or to the MR reference model, then an MR representation that isapproximated to the body structures of the patient results. Thisestablishes a relationship between the ascertained MR representation andthe fluoroscopic images of the patient, such that the MR reference datathat are approximated to the actual patient data or the adapted MRreference model can be registered to the fluoroscopic images. Thetransformation protocol also can be applied to the CT reference model inorder to obtain a CT reference model that is adapted to the actualpatient data.

In addition, the adapted generic model also can be registered to acorresponding patient-characteristic MR data set by means of a fixedregistration or transformation. The adapted generic model thus can beadditionally adapted or approximated to the actual patient structures,in particular the actual soft tissue structures. It is also possible toonly register the adapted three-dimensional MR reference model to thepatient-characteristic MR data set by means of a fixed registration, inorder to obtain a more accurate or more patient-specific MR model.

It is also possible to produce or provide a plurality of CT referencedata sets, from which the generic model is or can be generated. A CTreference data set, for example, can be selected as a CT main shapereference data set from the plurality of CT reference data sets. An MRmain shape reference data set corresponding to this CT main shapereference data set can be produced or provided, wherein the CT mainshape reference data set can be registered to the MR main shapereference data set.

The generic model thus can be generated exclusively from or by means ofCT reference data sets, such that the generic model can be accuratelyand quickly adapted to the patient-specific fluoroscopic images. Thegeneric model can be generated from the plurality of CT reference datasets, such as CT training reference data sets, and the CT main shapereference data set. One MR main shape reference data set preferably isregistered to the CT main shape reference data set, wherein acorrelation exists between the generic model and the MR main shapereference data set.

It is possible to produce a plurality of CT reference data sets of thethoracic vertebra of various persons, for example, such as two, three,four, five, six, seven, eight or more CT reference data sets. By way ofexample, six CT reference data sets of thoracic vertebrae of variouspersons can be read from a database or otherwise ascertained, whereinone of the six CT reference data sets preferably is selected as the CTmain shape reference data set. An MR main shape reference data set thatis registered to the CT main shape reference data set preferably also isread off from the database, or an MR main shape reference data set thatcorresponds to the CT main shape reference data set is produced and isregistered to the CT main shape reference data set. Based on the otherfive CT reference data sets, the generic model, for example, can beascertained only using the extracted surface information of the five CTreference data sets so as to produce a surface model as the genericmodel. One way of producing the generic model as a surface model isdescribed in: M. Fleute and S. Lavalle, “Building a complete surfacemodel from sparse data using statistical shape models: Application tocomputer-assisted knee surgery”, in MICCAI, pages 878-887, 1998, whichis incorporated by reference in its entirety.

By deforming at least a part of the generic model, the generic model canbe adapted to the patient-specific fluoroscopic images by means of anadaptation protocol or transformation protocol, such as athree-dimensional transformation protocol. Such three-dimensionaltransformation protocol describes or specifies how a part of the genericmodel or the entire generic model has to be shifted or repositioned inorder to achieve the greatest possible match between the generic modeland the patient-specific image data.

This transformation protocol, for example, can be applied to the entireMR main shape reference data set to obtain from the MR reference dataset an approximate patient-characteristic MR representation that isrelated to the fluoroscopic image data. The transformation protocol alsocan be analogously applied to the CT main shape reference data set, inorder to transform or deform its image data.

The transformation protocol also can be applied to a part of the MR mainshape reference data set that is registered to the CT main shapereference data set, or to a main shape reference data set formed fromthe CT main shape reference data set and the MR main shape referencedata set. The transformation protocol preferably is only applied to theregions or structures of the main shape reference data set or MR mainshape reference data set that can be definitively identified orreferenced in the fluoroscopic image data and/or the generic model, suchthat an accurate or reliable transformation can be ensured with respectto these points. The structures, such as soft tissue structures, musclesor skin structures, that are not displayed in the fluoroscopic imagesand/or the generic model (e.g., the generic model generated from the CTdata sets) can remain unchanged (e.g., they are not subjected to thetransformation). An MR main shape reference data set that is registeredto the CT main shape reference data set can be ascertained.Alternatively, a main shape reference data set that is formed from theCT main shape reference data set and the MR main shape reference dataset can be generated. In the generated data sets, only the structures orparts that were significantly adapted or deformed are adapted to thepatient-specific image data. The image data for which it is uncertainwhether a deformation is necessary, such as image data that cannot beidentified or displayed in the fluoroscopic images and/or the genericmodel, preferably remain unchanged.

The main shape reference data set approximated to the actual patientstructures or the MR main shape reference data set can be improved oradditionally adapted to the actual patient structures. This may beaccomplished by registering the already adapted main shape referencedata set or MR main shape reference data set to a correspondingpatient-characteristic MR data set by means of a fixed registration ortransformation. This enables the regions of the adapted MR main shapereference data set that initially remained unchanged to be filled in orchanged.

This approach exhibits an array of advantages. Non-patient-specific CTdata sets that are easy to ascertain or record can be used to producethe generic model. In this approach, only the main shape reference dataset comprises an MR main shape reference data set and a CT main shapereference data set, which results in a significant reduction in laborand costs. Also, only the data of the main shape reference data set thatalso can be displayed in the fluoroscopic images and/or the genericmodel, and the patient-specific position of which can thus be correctlyascertained to a high probability, may be changed based on theascertained transformation protocol. The fixed registration of theadapted main shape reference data set to the patient-specific MR dataset also represents a simple, accurate and quick process.

Various types of patient-characteristic data that can be used to adaptthe generic model are outlined below. Also, it is always possible to usecombinations of such data, referred to below as diagnostic data.

The patient-characteristic data can be x-ray image data, such as fromx-ray images produced beforehand or during the treatment, in particularbi-planar or multi-planar x-ray images. One example would be where x-rayimages are already available for the patient that were produced withinthe framework of previous examinations. Data concerning body structuresfrom these “old” x-ray images are particularly suitable if deviations inshape as compared to the generic model are to be factored in.

It is, however, also possible to produce individual x-ray images of thepatient even during the treatment and to then incorporate thisinformation into adapting the generic model. An advantage as compared toconventional “x-ray navigation” is that it is not necessary to produce alarge number of x-ray images, as used in x-ray image based navigation.By contrast, it is sufficient to produce only one or very few x-rayimages in order to adapt the generic model, which in addition can belimited to a very small portion of the body. This significantly reducesthe radiation load as compared to conventional x-ray navigation.

The above also applies similarly to computer tomography or nuclear spintomography image data. It is possible to use image data obtained fromtomography detections produced much earlier, but the information ofwhich is sufficient to suitably adapt the generic model.

It is not necessary, however, to use complicated patient-characteristicdetection data or diagnostic data in this way to sufficiently adapt thegeneric model. It can be perfectly sufficient to use acquired pointposition information on the body structure of the patient, in particularnatural or artificial landmarks. The patient-characteristic diagnosticdata, for example, can be just the distance between two landmarks (forexample bone extensions) which alone can provide sufficient informationas to how the generic model is to be restructured. Data concerning thesize, weight or body portion lengths or limb lengths of the patient canalso be used as a basis for to adapt the generic model.

The generic model can be adapted by one or more of the followingmethods:

-   -   manually adapting with the aid of image representation        assistance, in particular by displacing points and landmarks or        shifting, rotating, expanding or compressing the generic model        on a screen output by means of a user interface;    -   automatic image fusion methods that are in particular based on        automatically identifying particular anatomical features;    -   image data of the generic model, in particular digitally        reconstructed x-ray images, and image data from computer        tomography or nuclear spin tomography image data sets can be        superimposed or fused together.

A deformation and/or rotation protocol can be used as the transformationprotocol of the generic model.

The generic model thus can be fused with patient-specific information orimage data either automatically, for example by automaticallyidentifying particular anatomical features that are critical for fusing,or also manually, for example by shifting, rotating, and/orstretching/warping. If the generic model is fused with actual patientinformation with the aid of acquiring an indefinite number of items ofpoint information on the patient (landmarks), it is possible to use aso-called surface matching method, e.g., a computer-assisted imageadapting method, to fuse the image data. Detecting the diagnostic dataand adapting the generic model from the various methods described abovecan be combined such that in addition to the diagnostic data (forexample, intra-operatively acquired x-ray images), additional points onthe patient also are recorded in the form of landmarks or randomlyacquired points and used to accurately detect and adjust the position ofthe model or even its shape, so as to enhance navigation accuracy.

Generally speaking, the position data obtained by ascertaining thepatient-characteristic detection data, in particular by acquiringlandmark positions or by x-ray image recordings registered in anavigation system, can be used in the method to register the adaptedbody structure data in the navigation system and to graphicallyrepresent or use treatment apparatus or treatment-assisting apparatusregistered to the adapted body structure. In other words, the step ofdetecting the diagnostic data can be simultaneously used to register thepatient and the adapted generic model for navigation. As soon as thedata of the model have been fused with registered data, e.g., data whichhave been definitively determined in their spatial position, for exampleregistered fluoroscopic images of an x-ray navigation software, or assoon as the data of the model have been registered to landmarks, or acombination of both methods, they can be used for computer-assistedsurgery and for minimally invasive operations, e.g., by displayinginstruments or implants in relation to a fused model.

Also provided is a computer program which, when it is loaded onto acomputer or is running on a computer, performs a method as describedabove, and to a program storage medium or computer program productcomprising such program.

A device for registering a three-dimensional magnetic resonance (MR)data set to at least two fluoroscopic images of a patient comprises adata detection device, a navigation system for ascertaining thethree-dimensional spatial position of the data detection device, and acomputational unit such as a computer connected to the navigationsystem. Patient-specific detection data such as fluoroscopic images canbe recorded by the data detection device, wherein the navigation systemserves to ascertain the three-dimensional spatial position of the datadetection device relative to the body structure to be recorded.

The computational unit preferably is connected via a wire connection orwirelessly to the navigation system. All the method steps describedabove that utilize computational operations can be performed orascertained by the computational unit. The computational unit canascertain a three-dimensional generic model, in particular a surfacemodel, for bodies or body parts of various persons, wherein the genericmodel contains patient-specific body structure data. Thethree-dimensional generic model can contain or be based on at least onethree-dimensional MR reference data set or can at least be correlatedwith the three-dimensional MR reference data set. The computational unitcan change or deform or adapt the generic model based on the ascertainedtwo-dimensional patient-characteristic detection data by means of atransformation protocol for data-linking the body structure data of thethree-dimensional generic model to the two-dimensionalpatient-characteristic detection data. The computational unit can alsochange or adapt at least a part of the three-dimensional MR referencedata set by means of the transformation protocol, in order to generateor ascertain a patient-characteristic three-dimensional MR data setwhich is registered to the fluoroscopic images.

BRIEF DESCRIPTION OF THE DRAWINGS

The forgoing and other features of the invention are hereinafterdiscussed with reference to the drawing.

FIG. 1 is a flow diagram illustrating an exemplary method in accordancewith the invention.

FIG. 2 is a flow diagram illustrating another exemplary method inaccordance with the invention.

FIG. 3 illustrates an exemplary device for implementing the method inaccordance with the invention.

FIG. 4 is a block diagram of an exemplary computer system that can beused in the device of FIG. 3.

DETAILED DESCRIPTION

FIG. 1 is a flow diagram illustrating a first exemplary method forregistering patient data on the basis of generic models. At least twofluoroscopic images of a body region of a patient are initially recordedin step S10. These fluoroscopic images contain patient-specific datasuch as patient-specific structures or shapes. A non-patient-specificadaptive generic model, which, for example, can include a plurality ofdata sets such as CT data sets, MR data sets, x-ray data sets or otherdata sets, is adapted to the fluoroscopic image data in step S11 bymeans of a transformation protocol. The transformation protocol at leastpartially adapts the initially non-patient-specific generic model to theactual patient-specific structures apparent from the fluoroscopicimages. In the next step, step S12, the generic model, which has alreadybeen partially adapted, is registered with respect to a patient-specificMR data set, or conversely, the patient-specific MR data set isregistered with respect to the generic model that has already beenpartially adapted. Preferably, a rigid registration that does not deformthe generic model and, for example, can fill in previously indefinitestructures or regions is used. An MR reference data set contained in thegeneric model is therefore also registered to the patient-specific imagedata. In a subsequent step, step S13, it is possible to navigate basedon the fluoroscopic images, the generic model and the patient-specificMR data set.

FIG. 2 is a flow diagram illustrating a second exemplary method forregistering patient data on the basis of generic models. As explained inrelation to FIG. 1, fluoroscopic images of a patient are produced instep S20. A non-body-specific generic model also is ascertained that isbased on CT data sets of a plurality of individuals. This generic modelis adapted to the fluoroscopic images in step S21 by means of atransformation, such that those regions of the generic model aredeformed that are formed or shaped differently in the body-specificfluoroscopic images.

A transformation protocol is therefore ascertained in step S21 thatdescribes the deformation of the non-body-specific generic model foradapting it to the body-specific image data. By means of thistransformation protocol, an MR reference data set that is related to thegeneric model is deformed in step S22, wherein preferably only thoseregions of structures of the MR reference data set are deformed that arealso formed or displayed in the generic model. It is possible tonavigate based on the partially adapted MR reference data set alone.

Alternatively or additionally, the MR reference data set that hasalready been partially adapted is registered in step S23, preferablyrigidly or fixedly, to an ascertained patient-specific MR data set.Alternatively, the patient-specific MR data set is registered,preferably rigidly, to the MR reference data set that has already beenpartially adapted. The data sets are registered such that whilepreviously unchanged regions or regions of the MR reference data setthat are different relative to the MR data set are filled in or changed,the MR reference data set is not however deformed. The MR reference dataset is thus registered to the patient-specific data and to thefluoroscopic images. In a subsequent step, step 24, it is possible tonavigate based on the fluoroscopic images, the generic model and thepatient-specific MR data set.

FIG. 3 shows an embodiment of a device for implementing the methodsdescribed herein, comprising an x-ray device 2 formed as a C-arm, bymeans of which fluoroscopic images of a patient on whom a reference star10 is preferably arranged can be recorded (such as recordings of thethoracic vertebra 1 of a patient). The x-ray device comprises aradiation source 3, an image amplifier 4 and an x-ray screen or x-rayequipment 5, by means of which registered fluoroscopic images can beproduced. The device also comprises a navigation system 9, by means ofwhich the position of the x-ray device 2 with respect to the patient canbe ascertained by detecting the reference star 10 arranged on thepatient. The navigation system 9 is connected to a computer 7 whichcomprises a memory or database and can perform computational operationsneeded to perform the method in accordance with the invention.

Moving now to FIG. 4 there is shown a block diagram of an exemplarycomputer 7 that may be used to implement one or more of the methodsdescribed herein. The computer 7 may include a display 22 for viewingsystem information, and a keyboard 24 and pointing device 26 for dataentry, screen navigation, etc. A computer mouse or other device thatpoints to or otherwise identifies a location, action, etc., e.g., by apoint and click method or some other method, are examples of a pointingdevice 26. Alternatively, a touch screen (not shown) may be used inplace of the keyboard 24 and pointing device 26. The display 22,keyboard 24 and mouse 26 communicate with a processor via aninput/output device 28, such as a video card and/or serial port (e.g., aUSB port or the like).

A processor 30, such as an AMD Athlon 64® processor or an Intel PentiumIV® processor, combined with a memory 32 execute programs to performvarious functions, such as data entry, numerical calculations, screendisplay, system setup, etc. The memory 32 may comprise several devices,including volatile and non-volatile memory components. Accordingly, thememory 32 may include, for example, random access memory (RAM),read-only memory (ROM), hard disks, floppy disks, optical disks (e.g.,CDs and DVDs), tapes, flash devices and/or other memory components, plusassociated drives, players and/or readers for the memory devices. Theprocessor 30 and the memory 32 are coupled using a local interface (notshown). The local interface may be, for example, a data bus withaccompanying control bus, a network, or other subsystem.

The memory may form part of a storage medium for storing information,such as application data, screen information, programs, etc., part ofwhich may be in the form of a database. The storage medium may be a harddrive, for example, or any other storage means that can retain data,including other magnetic and/or optical storage devices. A networkinterface card (NIC) 34 allows the computer 7 to communicate with otherdevices.

A person having ordinary skill in the art of computer programming andapplications of programming for computer systems would be able in viewof the description provided herein to program a computer system 7 tooperate and to carry out the functions described herein. Accordingly,details as to the specific programming code have been omitted for thesake of brevity. Also, while software in the memory 32 or in some othermemory of the computer and/or server may be used to allow the system tocarry out the functions and features described herein in accordance withthe preferred embodiment of the invention, such functions and featuresalso could be carried out via dedicated hardware, firmware, software, orcombinations thereof, without departing from the scope of the invention.

Computer program elements of the invention may be embodied in hardwareand/or in software (including firmware, resident software, micro-code,etc.). The invention may take the form of a computer program product,which can be embodied by a computer-usable or computer-readable storagemedium having computer-usable or computer-readable program instructions,“code” or a “computer program” embodied in the medium for use by or inconnection with the instruction execution system. In the context of thisdocument, a computer-usable or computer-readable medium may be anymedium that can contain, store, communicate, propagate, or transport theprogram for use by or in connection with the instruction executionsystem, apparatus, or device. The computer-usable or computer-readablemedium may be, for example but not limited to, an electronic, magnetic,optical, electromagnetic, infrared, or semiconductor system, apparatus,device, or propagation medium such as the Internet. Note that thecomputer-usable or computer-readable medium could even be paper oranother suitable medium upon which the program is printed, as theprogram can be electronically captured, via, for instance, opticalscanning of the paper or other medium, then compiled, interpreted, orotherwise processed in a suitable manner. The computer program productand any software and hardware described herein form the various meansfor carrying out the functions of the invention in the exampleembodiments.

Although the invention has been shown and described with respect to acertain preferred embodiment or embodiments, it is obvious thatequivalent alterations and modifications will occur to others skilled inthe art upon the reading and understanding of this specification and theannexed drawings. In particular regard to the various functionsperformed by the above described elements (components, assemblies,devices, compositions, etc.), the terms (including a reference to a“means”) used to describe such elements are intended to correspond,unless otherwise indicated, to any element which performs the specifiedfunction of the described element (i.e., that is functionallyequivalent), even though not structurally equivalent to the disclosedstructure which performs the function in the herein illustratedexemplary embodiment or embodiments of the invention. In addition, whilea particular feature of the invention may have been described above withrespect to only one or more of several illustrated embodiments, suchfeature may be combined with one or more other features of the otherembodiments, as may be desired and advantageous for any given orparticular application.

1. A method for registering a non-patient-characteristicthree-dimensional magnetic resonance data set (MR data set) topatient-characteristic data, comprising: producing or providing anon-patient-characteristic three-dimensional generic model of a body orbody part containing body structure data; ascertaining or providingtwo-dimensional patient-characteristic detection data of a patient;using a transformation protocol for data-linking the body structure dataof the three-dimensional generic model to the two-dimensionalpatient-characteristic detection data to change or adapt the genericmodel of the body or body part based on the ascertained two-dimensionalpatient-characteristic detection data, wherein the three-dimensionalgeneric model is at least correlated with a three-dimensional MRreference data set; and changing or deforming at least a part of thethree-dimensional MR reference data set by using the transformationprotocol to generate a patient-characteristic three-dimensional MR dataset that is registered to the fluoroscopic images.
 2. The methodaccording to claim 1, wherein the patient-characteristic data includesat least two fluoroscopic images of a patient.
 3. The method accordingto claim 1, wherein producing or providing thenon-patient-characteristic three-dimensional generic model of the bodyor body part includes producing or providing a surface model of thenon-patient-characteristic three-dimensional generic model of a body orbody part.
 4. The method according to claim 1, wherein ascertaining orproviding two-dimensional patient-characteristic detection data of thepatient includes using at least two fluoroscopic images as thetwo-dimensional patient-characteristic detection data.
 5. The methodaccording to claim 1, wherein producing or providing thenon-patient-characteristic three-dimensional generic model includesforming the generic model from at least one computer tomographyreference data set (CT reference data set) and the at least one MR dataset, said CT reference data set and MR data set being registered to eachother.
 6. The method according to claim 1, wherein producing orproviding the non-patient-characteristic three-dimensional generic modelincludes forming the generic model from a plurality of CT reference datasets and a plurality of corresponding MR data sets, said CT referencedata set and MR data set being registered to each other.
 7. The methodaccording to claim 5, wherein producing the generic model includesforming from the at least one CT reference data set a three-dimensionalCT reference data representation that is correlated with the genericmodel and/or forming from the at least one MR reference data set athree-dimensional MR reference data representation that is correlatedwith the generic model.
 8. The method according to claim 6, whereinproducing the generic model includes forming from the at least one CTreference data set a three-dimensional CT reference data representationthat is correlated with the generic model and/or forming from the atleast one MR reference data set a three-dimensional MR reference datarepresentation that is correlated with the generic model.
 9. The methodaccording to claim 1, further comprising using a fixed registration ortransformation to register the adapted generic model to a correspondingpatient-characteristic MR data set.
 10. The method according to claim 1,wherein producing or providing a non-patient-characteristicthree-dimensional generic model includes: producing or providing aplurality of CT reference data sets; selecting or ascertaining a CTreference data set as a CT main shape reference data set from theplurality of CT reference data sets; producing or providing an MR mainshape reference data set corresponding to the CT main shape referencedata set; registering the CT main shape reference data set to the MRmain shape reference data set; and generating the generic model from theother CT reference data sets of the plurality of CT reference data sets.11. The method according to claim 10, further comprising applying thetransformation protocol of the generic model to at least a part of theMR main shape reference data set that is registered to the CT main shapereference data set to generate the patient-characteristicthree-dimensional MR data set.
 12. The method according to claim 11,further comprising applying the transformation protocol to the part ofthe MR main shape reference data set that contains structures which arealso displayed in the fluoroscopic images and/or the generic model. 13.The method according to claim 11, further comprising using a fixedregistration of transformation to register the generated MR data set toa corresponding patient-characteristic MR data set.
 14. The methodaccording to claim 12, further comprising using a fixed registration oftransformation to register the generated MR data set to a correspondingpatient-characteristic MR data set.
 15. The method according to claim 1,wherein using the transformation protocol for data-linking includesusing a deformation and/or rotation protocol as the transformationprotocol.
 16. The method according to claim 1, wherein the generic modelexhibits at least one of a typical and/or average body structure; astatistical model of a body structure; a plurality of body structures ofthe same type; a two-dimensional or three-dimensional data set of a bodystructure.
 17. The method according to claim 16, wherein exhibiting astatistical model of the body structure includes a statistical modelbased on statistical evaluations of an indefinite number of image datasets.
 18. The methods according to claim 16, wherein exhibiting atwo-dimensional or three-dimensional data set includes a geometricmodel.
 19. The method according to claim 1, wherein changing or adaptingthe generic model of the body or body part includes at least one of:manually adapting the generic model with the aid of image representationassistance; using an automatic image fusion method based onautomatically identifying particular anatomical features; superimposingor fusing image data of the generic model,
 20. The method according toclaim 19, wherein manually adapting includes adapting by displacingpoints and landmarks or shifting, rotating, expanding or compressing thegeneric model on a screen output by via a user interface.
 21. A computerprogram embodied on a machine readable medium for registering anon-patient-characteristic three-dimensional magnetic resonance data set(MR data set) to patient-characteristic data, comprising: code thatproduces or provides a non-patient-characteristic three-dimensionalgeneric model of a body or body part containing body structure data;code that ascertains or provides two-dimensional patient-characteristicdetection data of a patient; code that uses a transformation protocolfor data-linking the body structure data of the three-dimensionalgeneric model to the two-dimensional patient-characteristic detectiondata to change or adapt the generic model of the body or body part basedon the ascertained two-dimensional patient-characteristic detectiondata, wherein the three-dimensional generic model is at least correlatedwith a three-dimensional MR reference data set; and code that changes ordeforms at least a part of the three-dimensional MR reference data setby using the transformation protocol to generate apatient-characteristic three-dimensional MR data set that is registeredto the fluoroscopic images.
 22. A device for registering anon-patient-characteristic three-dimensional magnetic resonance data set(MR data set) to patient-characteristic detection data, comprising: adata detection device for recording at least two fluoroscopic imagescontaining two-dimensional patient-characteristic detection data; anavigation system for ascertaining a three-dimensional spatial positionof the data detection device relative to a body or body part to berecorded; and a computational unit communicatively coupled to thenavigation system, said computational unit configured to produce athree-dimensional generic model of a body or body part containing bodystructure data, wherein the three-dimensional generic model is at leastcorrelated with a three-dimensional MR reference data set; use means ofa transformation protocol for data-linking the body structure data ofthe three-dimensional generic model to the two-dimensionalpatient-characteristic detection data to change or adapt the genericmodel of the body or body part, based on the ascertained two-dimensionalpatient-characteristic detection data; and change or deform at least apart of the three-dimensional MR reference data set using thetransformation protocol to generate a patient-characteristicthree-dimensional MR data set that is registered to the fluoroscopicimages.